You are here

YUSAG Bracketology

Updated November 19th

By: Luke Benz

Welcome to YUSAG Bracketology! Below is our attempt to predict the NCAA Men's Basketball Tournament field of 68. Automatic bids are awarded to the highest ranked team in each conference, per our power-rankings. At-large bids are awarded to the 36 remaining teams with the best blend of several metrics. Those metrics are:

YUSAG Coefficient: Model coefficients for NCAA Hoops prediction model, used in our power rankings. More on model methodology can be found here

RPI: NCAA Rating Percentage Index. RPI is a stupid, outdated way to select tournament teams, yet the NCAA uses it anyway. Did we mention it's stupid? Note that the RPI we use is a projected end of season RPI that updates throughout the course of the season.

Strength of Record (SOR): We calculate strength of record by computing the difference in a team's win total and the number of wins we would expect the average Top-25 ranked team (per YUSAG Coefficient) to earn against a given team's schedule. We use projected end of season win total (which updates with each new game outcome) when computing Strength of Record to avoid one strange result skewing this metric

Wins Above Bubble (WAB): The difference in the number of wins a team has compared to the expected number of wins an average "bubble" team would earn against a given teams' schedule. We compute WAB by computing a team's win expected win difference against each of the at-large teams ranked 32-40 by YUSAG coefficient and averaging these differences

Using a weighted "blend" of the metrics, the teams are selected to the bracket.The current "blend" formula can be seen below.. Automatic bids are denoted by bold, while the "First Four" (last four at-large bids, worst four automatic bids) are denoted by italics. The raw values of these metrics for all 353 Division-1 teams can be found here . Teams are selected and seeded using a combination of logistic regression based at-large odds and linear regression to predict the seed of selected teams based on historical data since the 2015-2016 season.

We will be featured in the Bracket Matrix, a site that compares and evaluates over 100 bracketology rankings from all corners of the internet, if you're curious how these rankings stack up against other systems. Additionally, Ken Massey's site will be tracking how our model (and dozens of other models) fairs this season, so feel free to check out our progress there. The code used for this project can be found on GitHub and the methodology for this project can be found here.